lmshuizong

语音识别,有GUI界面，实现0~9数字语音识别(speaker identification)

基于负熵的盲源分离算法，可以用于语音的盲分离，提高语音信号质量(Negative entropy algorithm based on blind source separation, can be used to blind separation of speech, improve the quality of voice signal)

这 里主要对LMS算法及一些改进的LMS算法（NLMS算法、变步长LMS算法、变换域LMS算法）之间的不同点进行了比较，在传统的LMS算法的基础上发 展了LMS算法的应用。另一方面又从RLS算法的分析中对其与LMS算法的不同特性进行了比较。(Here mainly on the LMS algorithm and some improvements of the LMS algorithm (NLMS algorithm, variable step size LMS algorithm, transform domain LMS algorithm) between the different points of comparison, in the traditional LMS algorithm developed on the basis of the application of the LMS algorithm. On the other hand from the analysis of RLS algorithm and LMS algorithm for its different characteristics compared.)

语音信号的特征提取，语音信号的Mel倒谱特征（MFCC）的求解方法，语音信号的线性预测原理以及LPC特征的求解方法 (Speech signal feature extraction, speech signal characteristics of Mel cepstrum (MFCC) the solution, voice signals, as well as the principle of linear prediction characteristics of the LPC method)

adaptive modulation cm in speech coding

熵值越大则每个符号包含的平均信息量越大。有研究发现，在有噪声的语音信号中，语音信号的熵和噪声信号的熵存在着较大的差异，对噪声信号来说在整个频带内分布相对平坦，熵值小，语音信号集中在某些特定频段内，熵值大。因此利用这个差异可以区分噪音段和语音段。(The greater the entropy is, the greater the average information of each symbol is. It is found that, in noisy speech signals, the entropy of speech signals and the entropy of noise signals are quite different. For noisy signals, the distribution is relatively flat in the whole frequency band, and the entropy value is small. The speech signal is concentrated in some specific frequency bands, and the entropy value is large. So the difference can be used to distinguish the noise segment and the speech segment.)

回声消除算法比较，仿射投影APA与NLMS算法比较(Echo cancellation apa nlms)

评书,语音小说下载程序,修改一下可批量下载(Storytelling, voice novels download, modify available for bulk download)

一个完整的基于Matlab的DTW模型算法及高效算法程序，能快速识别数字0-9,运行testdtw即可。(An excellent MATLAB program for the algorithm as a DTW model. It can recognise the number of 0-9. Try it, just run testdtw.)

本文介绍了基于麦克风阵列的声源定位算法，给初学者有很大的帮助(This article describes the microphone array based sound source localization algorithm, a great help for beginners)